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VP Operations, Wylie Indicators Ltd.

" We are happy with our interaction with KritiKal. They have a good team with high delivery capability of cutting edge technologies, which help them deliver complex projects within c..."

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Managing Director, Real Time Systems

" I believe that traffic conditions in developing countries in general and India in particular are so different from those in the West that we need to develop our own analysis and pl..."

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TRIPP, IIT Delhi

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Ex Scientist, DRDO ; Dean R&D, NMIT

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Vice President (Systems)

" ...by leveraging the vision capabilities and product development experience of KritiKal, we will take our customers’ experience to the next level. We have chosen KritiKal as our..."

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CEO, Heartwood Studios

" "Last two years have been working with KritiKal Solutions in defining a tool which helps in traffic planning for our vehicle mix. The tool delivered by them is helping our team for..."

Dr. Geetam Tiwari
TRIPP, IIT Delhi

Optical Character Recognition

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OCR is used for translating images of typewritten or printed text (usually captured by a scanner or camera) into machine-readable form with a standard encoding scheme. Different techniques for OCR have been developed and used under different application scenarios. Some of the applications include conversion of legacy documents to an e-format for document imaging systems, License Plate Reader System for capturing the license number of vehicles. And high speed OCR system for domain specific applications.

Features

Capability: Our Imaging team has experience to design custom OCR solutions based on the client’s specific requirements. The OCR Engine is independent from font type and size to recognize and can read virtually every kind of printed text. It reads:

Digits
Uppercase letters
Lowercase letters
Symbols

It is able to recognize characters, words, text lines, paragraphs or full pages. It's able to split and recognize glued characters and to glue and recognize broken characters, too. To better the performance of OCR engine it pre-process the image with de-skewing and normalization techniques.

Accuracy: the OCR engine accuracy is 100% when the print and image quality are good. Even if the image quality is medium, the error rate is usually very low.

Speed: 200 / 600 CPS, depending on cpu speed.

Input: Color, gray scale or bi tonal images with a 200 DPI or greater resolution can be used as input. Better performances are obtained using gray scale image with 300 DPI resolution since the ocr engine works natively in gray scale.

Output: the output includes the ASCII or UNICODE code, the confidence level,

Platform: the OCR Engine supports Linux and Windows platforms.

Applications

The OCR Engine finds useful application in the following areas:-

Traffic & transportation industry
License plate recognition system
Container number identification
Automatic recording of the text written on the vehicle surface
Industrial Inspection
Document imaging

Optical Character Recognition

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